A method for rapidly evaluating reliability and predicting remaining useful life using two-dimensional convolutional neural network with signal conversion

Journal of Mechanical Science and Technology - Real-time monitoring and rapid evaluation of bearing operating conditions, especially for the reliability evaluation and remaining useful life (RUL)...     

Physical Stability of Octenyl Succinate–Modified Polysaccharides and Whey Proteins for Potential Use as Bioactive Carriers in Food Systems

The high cost and potential toxicity of biodegradable polymers like poly(lactic‐co‐glycolic)acid (PLGA) has increased the interest in natural and modified biopolymers as bioactive carriers. This study characterized the physical stability (water sorption and state transition behavior) of selected starch and proteins: octenyl succinate–modified depolymerized waxy corn starch (DWxCn), waxy rice starch (DWxRc), phytoglycogen, whey protein concentrate (80%, WPC), whey protein isolate (WPI), and α‐lactalbumin (α‐L) to determine their potential as carriers of bioactive compounds under different environmental conditions. After enzyme modification and particle size characterization, glass transition temperature and moisture isotherms were used to characterize the systems. DWxCn and DWxRc had increased water sorption compared to native starch. The level of octenyl succinate anhydrate (OSA) modification (3% and 7%) did not reduce the water sorption of the DWxCn and phytoglycogen samples. The Guggenheim–Andersen–de Boer model indicated that native waxy corn had significantly (P < 0.05) higher water monolayer capacity followed by 3%‐OSA‐modified DWxCn, WPI, 3%‐OSA‐modified DWxRc, α‐L, and native phytoglycogen. WPC had significantly lower water monolayer capacity. All Tg values matched with the solid‐like appearance of the biopolymers. Native polysaccharides and whey proteins had higher glass transition temperature (Tg) values. On the other hand, depolymerized waxy starches at 7%‐OSA modification had a “melted” appearance when exposed to environments with high relative humidity (above 70%) after 10 days at 23 °C. The use of depolymerized and OSA‐modified polysaccharides blended with proteins created more stable blends of biopolymers. Hence, this biopolymer would be suitable for materials exposed to high humidity environments in food applications.     

Experimental and numerical analysis of the influence of cable tray arrangements on the resulting mass loss rate and fire spreading

In the context of industrial buildings and power plants, electrical installations and cable trays represent a main fuel load and a potential initial fire source due to possible short circuits or comparable malfunction. Furthermore, a fire can spread from one tray to additional trays mounted above and/or horizontally on one tray. Because of the high significance of cable fires, several research projects have been carried out, investigating the fire behaviour of cables from small‐scale tests, eg, the cone calorimeter, up to large‐scale tests, analysing complete cable tray constructions. The goal of the work presented in this paper is the extension of the knowledge regarding the influence of geometrical parameters like the packing density and tray distance on the burning behaviour and fire spread of cable tray installations. The results are considered, together with test results from the literature, to quantify the main physical parameters describing the burning behaviour. In a next step, the general applicability of these parameters as input data for the parametrization of the source term of numerical simulations is shown. The test results show that the burning behaviour and the fire spreading highly depend on the cable arrangement of the cables on the cable tray, in combination with other boundary conditions. By applying the results as input for a fire simulation, the mass loss rate is considered appropriately.     

Distributed learning consensus control based on neural networks for heterogeneous nonlinear multiagent systems

This paper considers a novel distributed iterative learning consensus control algorithm based on neural networks for the control of heterogeneous nonlinear multiagent systems. The system's unknown nonlinear function is approximated by suitable neural networks; the approximation error is countered by a robust term in the control. Two types of control algorithms, both of which utilize distributed learning laws, are provided to achieve consensus. In the provided control algorithms, the desired reference is considered to be an unknown factor and then estimated using the associated learning laws. The consensus convergence is proven by the composite energy function method. A numerical simulation is ultimately presented to demonstrate the efficacy of the proposed control schemes.     

Electrocatalytic Reduction of CO2 to Ethylene by Molecular Cu‐Complex Immobilized on Graphitized Mesoporous Carbon

The electrochemical reduction of carbon dioxide (CO₂) to hydrocarbons is a challenging task because of the issues in controlling the efficiency and selectivity of the products. Among the various transition metals, copper has attracted attention as it yields more reduced and C2 products even while using mononuclear copper center as catalysts. In addition, it is found that reversible formation of copper nanoparticle acts as the real catalytically active site for the conversion of CO₂ to reduced products. Here, it is demonstrated that the dinuclear molecular copper complex immobilized over graphitized mesoporous carbon can act as catalysts for the conversion of CO₂ to hydrocarbons (methane and ethylene) up to 60%. Interestingly, high selectivity toward C2 product (40% faradaic efficiency) is achieved by a molecular complex based hybrid material from CO₂ in 0.1 m KCl. In addition, the role of local pH, porous structure, and carbon support in limiting the mass transport to achieve the highly reduced products is demonstrated. Although the spectroscopic analysis of the catalysts exhibits molecular nature of the complex after 2 h bulk electrolysis, morphological study reveals that the newly generated copper cluster is the real active site during the catalytic reactions.